System and Computer Program Product to Predict Edges in a Non-Cumulative Graph

1. A computer program product comprising a tangible computer useable storage medium including computer usable program code for predicting edges of a graph, based on a sequence of non-cumulative previous occurrences of said graph, said computer program product including: computer usable program code for obtaining said sequence of non-cumulative previous occurrences of said graph; computer usable program code for extracting topological properties of each of said previous occurrences of said graph; computer usable program code for computing topological similarities between each of said previous occurrences of said graph, based on said topological properties; and computer usable program code for predicting said edges of a future instance of said graph by computing a score for each possible edge of said graph, based upon said topological similarities, wherein the score comprises, for each edge, a probability of existing in the future instance and wherein each of said scores is weighted equally.

2. The computer program product of claim 1 , wherein said probabilities for said possible edges indicate importance of a given one of said edges to integrity of topology of a given occurrence of said graph.

3. The computer program product of claim 2 , wherein said given occurrence of said graph comprises one of said previous occurrences of said graph.

4. The computer program product of claim 2 , wherein said given occurrence of said graph comprises a predicted occurrence of said graph based upon said predicted edges.

5. A system for predicting edges of a graph, based on a sequence of non-cumulative previous occurrences of said graph, said system comprising: a memory; and at least one processor, coupled to said memory, and operative to obtain said sequence of non-cumulative previous occurrences of said graph; extract topological properties of each of said previous occurrences of said graph; compute topological similarities between each of said previous occurrences of said graph, based on said topological properties; and predict said edges of a future instance of said graph by computing a score for each possible edge of said graph, based upon said topological similarities, wherein the score comprises, for each edge, a probability of existing in the future instance and wherein each of said scores is weighted equally.

6. The system of claim 5 , wherein said probabilities for said possible edges indicate importance of a given one of said edges to integrity of topology of a given occurrence of said graph.

7. The system of claim 6 , wherein said given occurrence of said graph comprises one of said previous occurrences of said graph.

8. The system of claim 6 , wherein said given occurrence of said graph comprises a predicted occurrence of said graph based upon said predicted edges.

9. A system for predicting edges of a graph, based on a sequence of non-cumulative previous occurrences of said graph, said system comprising: means for obtaining said sequence of non-cumulative previous occurrences of said graph; means for extracting topological properties of each of said previous occurrences of said graph; means for computing topological similarities between each of said previous occurrences of said graph, based on said topological properties; and means for predicting said edges of a future instance of said graph by computing a score for each possible edge of said graph, based upon said topological similarities, wherein the score comprises, for each edge, a probability of existing in the future instance and wherein each of said scores is weighted equally.

10. The system of claim 9 , wherein said probabilities for said possible edges indicate importance of a given one of said edges to integrity of topology of a given occurrence of said graph.

11. The system of claim 10 , wherein said given occurrence of said graph comprises one of said previous occurrences of said graph.

12. The system of claim 10 , wherein said given occurrence of said graph comprises a predicted occurrence of said graph based upon said predicted edges.

13. The system of claim 9 , wherein said means for extracting topological properties of each of said previous occurrences of said graph comprises: means for building a matrix corresponding to each of said previous occurrences of said graph; and means for finding a set of paths, if any, between every node in each of said matrices corresponding to each of said previous occurrences of said graph.